S22-140 Efficient Analog Backpropagation Training Architecture for Photonic Neural Networks Stanford researchers design and demonstrate a novel in situ backpropagation training algorithm for photonic implementations of neural networks. Sunil Pai David Miller Olav Solgaard Shanhui Fan Tyler Hughes Ian Williamson Momchil Minkov Zhanghao Sun
S20-531 Resonant Scanning Design and Control for Fast Spatial Sampling Despite their compact form factor and low power consumption, resonant scanners have not been widely applied to LiDAR due to their scanning trajectory. Zhanghao Sun Ron Quan Olav Solgaard Sandra Manosalvas-Kjono
S19-023 Method and Apparatus for Evaluating Electrostatic or Nonlinear Devices Researchers at Stanford have developed methods for evaluating the position of a micro-electromechanical system (MEMS) device in terms of phase and/or amplitude characteristics. Ron Quan Olav Solgaard Sandra Manosalvas-Kjono Zhanghao Sun